# make kable table with consistent formatting
make_table <- function(..., title = "", col_names = c("")) {
title <- paste0("<center><span style = 'font-size:150%;color:black'><b>",
title,
"</span></b><center>")
as_tibble(...) %>%
kbl(caption = title,
col.names = col_names) %>%
kable_material() %>%
row_spec(row=0, background = "#43494C" , color = "white", bold = TRUE)
}## Loading in data
endowment_data <- read_rds(here("data", "endowments_by_most_recent_filings.RDS"))
names <- read_csv(here("data", "companies.csv")) %>%
## Dealing with EINs reading in without zero in front
mutate(EIN = as.character(ein),
EIN = case_when(
nchar(EIN) == 8 ~ paste("0", EIN, sep =""),
TRUE ~ EIN
)) %>%
select(-ein)## Rows: 308 Columns: 3
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): organization_name
## dbl (2): EIN, ein
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Calculating Percent Change
Including Investments
(End Year Balance - Beginning Year Balance) / Beginning Year Balance * 100
If EYB is larger, positive result. Meaning there was a INCREASE in total funds.
If BYB is larger, negative result. Meaning a DECREASE in total funds.
If result is above 100, the fund was at least DOUBLED.
#### USE THIS
## (EYB - BYB)/BYB * 100
## Rose has notes on her choice for this calculation
pct_change_ds <- endowment_data %>%
filter(!is.na(BeginningYearBalanceAmt)) %>%
mutate(change = EndYearBalanceAmt - BeginningYearBalanceAmt,
pct_change = change/BeginningYearBalanceAmt * 100) %>%
arrange(desc(pct_change)) %>%
left_join(names, by = "EIN")REMOVING Investments
(End Year Balance - Investment Earnings or Losses Amount - Beginning Year Balance) / Beginning Year Balance * 100
Positive result: INCREASE in total funds.
Negative result: DECREASE in total funds.
If result is above 100, the fund was at least DOUBLED.
#### USE THIS
## (EYB - INV - BYB)/BYB * 100
## Rose has notes on her choice for this calculation
pct_change_inv_ds <- endowment_data %>%
filter(!is.na(BeginningYearBalanceAmt)) %>%
mutate(InvestmentEarningsOrLossesAmt = ifelse(is.na(InvestmentEarningsOrLossesAmt), 0, InvestmentEarningsOrLossesAmt)) %>%
mutate(change = EndYearBalanceAmt - InvestmentEarningsOrLossesAmt - BeginningYearBalanceAmt,
pct_change = change/BeginningYearBalanceAmt * 100) %>%
arrange(desc(pct_change)) %>%
left_join(names, by = "EIN")Summarizing Information
With investments
# Basic summary stats
pct_change_ds %>%
filter(!is.na(pct_change) & pct_change != Inf) %>%
summarize(avg_pct_change = mean(pct_change),
median_pct_change = median(pct_change),
sd_pct_change = sd(pct_change))pct_change_ds %>%
filter(!is.na(pct_change) & pct_change != Inf) %>%
group_by(EIN) %>%
summarize(avg_pct_change = mean(pct_change),
median_pct_change = median(pct_change),
sd_pct_change = sd(pct_change))# Basic histogram summarizing it
ggplot(pct_change_ds, aes(x = pct_change)) +
geom_histogram(binwidth = 20) +
xlab("% Change\n(EYB - BYB) / BYB * 100") +
ggtitle(label = "Percentage of Change in Endowment Balance", subtitle = "Red Line indicates 100%") +
theme_classic() +
geom_vline(xintercept = 100, color = "maroon", linetype = "dotted")## Histogram with cutoff of 200%
ggplot(pct_change_ds, aes(x = pct_change)) +
geom_histogram(binwidth = 5) +
xlab("% Change\n(EYB - BYB) / BYB * 100") +
xlim(-100, 200) +
ggtitle(label = "Percentage of Change in Endowment Balance") +
theme_classic()pct_change_ds %>%
filter(pct_change != Inf) %>%
select(organization_name, fiscal_year, pct_change) %>%
make_table(title = "Percentage of Change in Endowment Balance", col_names = c("Name", "Fiscal Year", "% Change")) %>%
scroll_box(height = "450px")| Name | Fiscal Year | % Change |
|---|---|---|
| Joffrey Ballet | 2015 | 3091.4016854 |
| Fort Wayne Ballet | 2014 | 1897.2429619 |
| First State Ballet Theatre | 2012 | 1448.0762683 |
| Ballet Arizona | 2016 | 586.1374894 |
| Orlando Ballet | 2017 | 552.8554949 |
| Ballet Arizona | 2015 | 493.1015099 |
| Ballet Hispanico | 2021 | 432.1555786 |
| Nashville Ballet | 2011 | 288.7391599 |
| First State Ballet Theatre | 2020 | 242.6848638 |
| Milwaukee Ballet | 2011 | 212.5546600 |
| Atlanta Ballet | 2017 | 207.7002614 |
| Orlando Ballet | 2018 | 206.9063832 |
| Nashville Ballet | 2016 | 206.2101382 |
| Grand Rapids Ballet | 2015 | 186.0427033 |
| Richmond Ballet | 2016 | 178.0161483 |
| Charlotte Ballet | 2013 | 171.7520288 |
| Joffrey Ballet | 2019 | 146.9046722 |
| Texas Ballet Theater | 2015 | 133.5240000 |
| The Charleston Ballet | 2013 | 132.1823138 |
| Dayton Ballet | 2018 | 118.1185754 |
| Ballet Austin | 2013 | 111.9610260 |
| Miami City Ballet | 2021 | 103.3796951 |
| Ballet Memphis | 2018 | 100.3575811 |
| Ballet Memphis | 2012 | 94.1089954 |
| Joffrey Ballet | 2020 | 90.8216917 |
| Ballet Austin | 2017 | 90.2783217 |
| Texas Ballet Theater | 2018 | 85.8401625 |
| BalletMet | 2018 | 85.0249761 |
| Atlanta Ballet | 2016 | 81.8387443 |
| The Tallahassee Ballet | 2011 | 74.5093458 |
| First State Ballet Theatre | 2019 | 69.9900000 |
| Richmond Ballet | 2018 | 57.4030070 |
| Ballet Hispanico | 2014 | 54.7692390 |
| First State Ballet Theatre | 2016 | 53.2556470 |
| American Repertory Ballet | 2014 | 51.6506759 |
| Atlanta Ballet | 2012 | 47.7865882 |
| Dayton Ballet | 2019 | 47.3628143 |
| Ballet Des Moines | 2018 | 40.4800000 |
| Richmond Ballet | 2020 | 39.8449675 |
| The Sarasota Ballet | 2016 | 36.6266667 |
| Boston Ballet | 2014 | 36.2295633 |
| Eugene Ballet | 2021 | 35.3676599 |
| The Tallahassee Ballet | 2014 | 35.2860183 |
| Richmond Ballet | 2019 | 34.8263002 |
| American Repertory Ballet | 2013 | 34.4003625 |
| First State Ballet Theatre | 2017 | 32.2270270 |
| Nashville Ballet | 2013 | 31.9611808 |
| Ballet Memphis | 2014 | 29.0814635 |
| New Mexico Ballet Company | 2019 | 28.7289611 |
| Aspen Santa Fe Ballet | 2017 | 27.9853981 |
| Richmond Ballet | 2017 | 27.4751409 |
| Miami City Ballet | 2018 | 26.9869980 |
| Ballet Memphis | 2017 | 26.3332143 |
| BalletMet | 2014 | 25.3577272 |
| Kansas City Ballet | 2011 | 23.4046965 |
| BalletMet | 2019 | 22.9766213 |
| Ballet Memphis | 2011 | 21.9748193 |
| Joffrey Ballet | 2016 | 20.8230683 |
| Kansas City Ballet | 2012 | 20.7916223 |
| The Charleston Ballet | 2011 | 20.3422772 |
| Pittsburgh Ballet Theatre | 2021 | 20.2563462 |
| Joffrey Ballet | 2018 | 20.1054139 |
| Charlotte Ballet | 2014 | 19.2067643 |
| The Washington Ballet | 2011 | 19.0694795 |
| San Francisco Ballet | 2017 | 18.7877861 |
| Nashville Ballet | 2017 | 18.7510970 |
| Pittsburgh Ballet Theatre | 2014 | 18.4707163 |
| Pacific Northwest Ballet | 2011 | 17.1031688 |
| Alvin Ailey American Dance Theater | 2011 | 16.9142437 |
| San Francisco Ballet | 2013 | 16.9015314 |
| The Washington Ballet | 2014 | 16.5357705 |
| Grand Rapids Ballet | 2020 | 16.5116257 |
| Dayton Ballet | 2017 | 16.4112620 |
| Houston Ballet | 2011 | 16.4010185 |
| New York City Ballet | 2018 | 16.3644199 |
| Joffrey Ballet | 2017 | 15.8506700 |
| Houston Ballet | 2017 | 15.6387481 |
| Houston Ballet | 2014 | 15.6082029 |
| Oregon Ballet Theatre | 2013 | 15.5103905 |
| Tulsa Ballet | 2018 | 15.3823425 |
| Boston Ballet | 2018 | 15.2551406 |
| Aspen Santa Fe Ballet | 2016 | 15.1095158 |
| Alvin Ailey American Dance Theater | 2014 | 15.0948805 |
| Ballet Arizona | 2017 | 15.0358519 |
| Pacific Northwest Ballet | 2017 | 15.0137712 |
| American Ballet Theatre | 2017 | 14.9425672 |
| The Charleston Ballet | 2014 | 14.9236822 |
| Kansas City Ballet | 2015 | 14.6091861 |
| Tulsa Ballet | 2015 | 14.4923885 |
| San Francisco Ballet | 2014 | 14.4355515 |
| Kansas City Ballet | 2019 | 14.2884428 |
| Charlotte Ballet | 2011 | 14.2224810 |
| Tulsa Ballet | 2019 | 14.0998602 |
| Kansas City Ballet | 2013 | 13.9762729 |
| Orlando Ballet | 2019 | 13.8649901 |
| Kansas City Ballet | 2014 | 13.8566871 |
| Atlanta Ballet | 2018 | 13.6920172 |
| Pittsburgh Ballet Theatre | 2018 | 13.4902430 |
| Houston Ballet | 2013 | 13.3539124 |
| Pittsburgh Ballet Theatre | 2011 | 13.3538665 |
| Tulsa Ballet | 2011 | 13.2967451 |
| Alvin Ailey American Dance Theater | 2013 | 13.2026403 |
| New York City Ballet | 2017 | 13.0492346 |
| Tulsa Ballet | 2017 | 12.8725445 |
| American Ballet Theatre | 2019 | 12.8340039 |
| The Tallahassee Ballet | 2015 | 12.7775722 |
| The Washington Ballet | 2013 | 12.7552838 |
| Milwaukee Ballet | 2014 | 12.4200913 |
| New York City Ballet | 2014 | 12.3479692 |
| Tulsa Ballet | 2013 | 11.7754847 |
| Madison Ballet | 2014 | 11.6614781 |
| Alvin Ailey American Dance Theater | 2017 | 11.5365116 |
| Alvin Ailey American Dance Theater | 2012 | 11.3682085 |
| Atlanta Ballet | 2015 | 11.3598829 |
| Grand Rapids Ballet | 2019 | 11.2809947 |
| Richmond Ballet | 2014 | 10.9079435 |
| The Charleston Ballet | 2017 | 10.7069912 |
| The Tallahassee Ballet | 2013 | 10.4979253 |
| Boston Ballet | 2011 | 10.3925842 |
| Charlotte Ballet | 2017 | 10.3333680 |
| New York City Ballet | 2011 | 10.0181422 |
| Pacific Northwest Ballet | 2013 | 9.8291806 |
| Boston Ballet | 2017 | 9.7115934 |
| American Ballet Theatre | 2013 | 9.5641764 |
| Fort Wayne Ballet | 2016 | 9.5012117 |
| Charlotte Ballet | 2015 | 9.1252970 |
| Ballet Austin | 2020 | 8.9689362 |
| American Ballet Theatre | 2020 | 8.9365465 |
| Nevada Ballet Theatre | 2011 | 8.9183455 |
| Ballet Austin | 2014 | 8.7657433 |
| Milwaukee Ballet | 2017 | 8.6823347 |
| Ballet West | 2015 | 8.5436426 |
| Charlotte Ballet | 2016 | 8.5301897 |
| Milwaukee Ballet | 2013 | 8.4440836 |
| Madison Ballet | 2017 | 8.2709975 |
| Ballet West | 2020 | 8.0887426 |
| New York City Ballet | 2013 | 8.0655265 |
| Charlotte Ballet | 2018 | 8.0057600 |
| American Ballet Theatre | 2012 | 7.9849386 |
| Boston Ballet | 2019 | 7.8186556 |
| Pacific Northwest Ballet | 2014 | 7.7515053 |
| The Charleston Ballet | 2018 | 7.7078009 |
| Kansas City Ballet | 2017 | 7.6710943 |
| Miami City Ballet | 2017 | 7.4251152 |
| Ballet Hispanico | 2011 | 7.4065897 |
| Tulsa Ballet | 2020 | 7.2630153 |
| Pittsburgh Ballet Theatre | 2017 | 7.1356111 |
| Aspen Santa Fe Ballet | 2012 | 7.0179265 |
| Boston Ballet | 2020 | 6.8383787 |
| Grand Rapids Ballet | 2017 | 6.7800620 |
| Madison Ballet | 2011 | 6.7615068 |
| Pennsylvania Ballet | 2011 | 6.6593049 |
| The Tallahassee Ballet | 2017 | 6.6393657 |
| Boston Ballet | 2016 | 6.4755945 |
| The Sarasota Ballet | 2017 | 6.4328584 |
| New Mexico Ballet Company | 2018 | 6.3933881 |
| Madison Ballet | 2013 | 6.3250010 |
| Ballet Des Moines | 2019 | 6.2713554 |
| Miami City Ballet | 2014 | 6.2446692 |
| Oregon Ballet Theatre | 2015 | 6.1461577 |
| Pacific Northwest Ballet | 2018 | 6.0970879 |
| Oregon Ballet Theatre | 2014 | 6.0199280 |
| Fort Wayne Ballet | 2015 | 5.9063870 |
| Aspen Santa Fe Ballet | 2011 | 5.8574809 |
| Pittsburgh Ballet Theatre | 2013 | 5.8355538 |
| Grand Rapids Ballet | 2018 | 5.6995093 |
| The Sarasota Ballet | 2020 | 5.3797096 |
| Nashville Ballet | 2014 | 5.3783928 |
| Milwaukee Ballet | 2018 | 5.3251625 |
| Pacific Northwest Ballet | 2020 | 5.2552006 |
| Tulsa Ballet | 2016 | 5.1996153 |
| Madison Ballet | 2018 | 5.1952964 |
| Ballet Memphis | 2013 | 5.1619171 |
| San Francisco Ballet | 2018 | 5.0127410 |
| Grand Rapids Ballet | 2014 | 4.9689028 |
| Ballet Hispanico | 2017 | 4.8257031 |
| Tulsa Ballet | 2014 | 4.7509696 |
| Ballet Austin | 2018 | 4.6407201 |
| Miami City Ballet | 2013 | 4.5466778 |
| Aspen Santa Fe Ballet | 2013 | 4.4768989 |
| Oregon Ballet Theatre | 2019 | 4.1823644 |
| Ballet Hispanico | 2013 | 4.1596925 |
| American Ballet Theatre | 2015 | 3.9081263 |
| Richmond Ballet | 2015 | 3.7696127 |
| Pennsylvania Ballet | 2014 | 3.5578845 |
| Alvin Ailey American Dance Theater | 2019 | 3.5551869 |
| Houston Ballet | 2018 | 3.5239698 |
| The Tallahassee Ballet | 2019 | 3.4501860 |
| Oregon Ballet Theatre | 2017 | 3.4233093 |
| The Tallahassee Ballet | 2018 | 3.2518997 |
| Ballet Quad Cities | 2017 | 3.2100411 |
| Nashville Ballet | 2018 | 3.1497842 |
| Boston Ballet | 2013 | 3.0250379 |
| Houston Ballet | 2019 | 3.0126539 |
| Richmond Ballet | 2013 | 2.9551103 |
| Ballet West | 2016 | 2.9479559 |
| Grand Rapids Ballet | 2011 | 2.9305635 |
| Pennsylvania Ballet | 2017 | 2.7458153 |
| Ballet Austin | 2019 | 2.7039028 |
| Alvin Ailey American Dance Theater | 2018 | 2.6520142 |
| Oregon Ballet Theatre | 2016 | 2.6351387 |
| Pacific Northwest Ballet | 2019 | 2.5299841 |
| Ballet West | 2019 | 2.5020351 |
| Ballet Austin | 2012 | 2.3668865 |
| Ballet Austin | 2015 | 2.0739029 |
| Ballet West | 2014 | 2.0511082 |
| Eugene Ballet | 2020 | 2.0266667 |
| Alvin Ailey American Dance Theater | 2015 | 2.0168085 |
| Oregon Ballet Theatre | 2020 | 1.9913020 |
| Grand Rapids Ballet | 2013 | 1.7112000 |
| Oregon Ballet Theatre | 2021 | 1.5619387 |
| The Alabama Ballet | 2017 | 1.5438912 |
| Ballet Hispanico | 2019 | 1.5405288 |
| Nevada Ballet Theatre | 2013 | 1.3945270 |
| Nashville Ballet | 2015 | 1.3707995 |
| Kansas City Ballet | 2016 | 1.3182366 |
| Miami City Ballet | 2019 | 1.1650569 |
| Alvin Ailey American Dance Theater | 2020 | 1.1173579 |
| Boston Ballet | 2012 | 1.1171575 |
| San Francisco Ballet | 2015 | 1.1010216 |
| Madison Ballet | 2020 | 1.0503166 |
| Ballet Arizona | 2014 | 0.9960259 |
| Pennsylvania Ballet | 2020 | 0.9848159 |
| Nevada Ballet Theatre | 2018 | 0.9818432 |
| Fort Wayne Ballet | 2017 | 0.9437819 |
| Pennsylvania Ballet | 2018 | 0.8212002 |
| BalletMet | 2011 | 0.8065975 |
| Pittsburgh Ballet Theatre | 2019 | 0.7669528 |
| Colorado Ballet | 2011 | 0.6399047 |
| Nashville Ballet | 2020 | 0.6340668 |
| Pacific Northwest Ballet | 2015 | 0.6277229 |
| The Alabama Ballet | 2020 | 0.5951924 |
| Texas Ballet Theater | 2019 | 0.5813097 |
| Texas Ballet Theater | 2020 | 0.5742863 |
| Colorado Ballet | 2015 | 0.5500000 |
| Fort Wayne Ballet | 2019 | 0.4949803 |
| Ballet Hispanico | 2018 | 0.4786320 |
| American Ballet Theatre | 2010 | 0.3281092 |
| Milwaukee Ballet | 2015 | 0.2558318 |
| Ballet Quad Cities | 2018 | 0.2475248 |
| New Mexico Ballet Company | 2020 | 0.2184921 |
| Oregon Ballet Theatre | 2018 | 0.1654999 |
| Ballet Hispanico | 2016 | 0.1309318 |
| New York City Ballet | 2019 | 0.0809932 |
| Texas Ballet Theater | 2017 | 0.0285424 |
| BalletMet | 2012 | 0.0266534 |
| Texas Ballet Theater | 2016 | 0.0199837 |
| Dance Theatre of Harlem | 2011 | 0.0000000 |
| Dance Theatre of Harlem | 2012 | 0.0000000 |
| Dance Theatre of Harlem | 2013 | 0.0000000 |
| Dance Theatre of Harlem | 2014 | 0.0000000 |
| Dance Theatre of Harlem | 2015 | 0.0000000 |
| Dance Theatre of Harlem | 2016 | 0.0000000 |
| Dance Theatre of Harlem | 2017 | 0.0000000 |
| Dance Theatre of Harlem | 2018 | 0.0000000 |
| Dance Theatre of Harlem | 2019 | 0.0000000 |
| Dance Theatre of Harlem | 2020 | 0.0000000 |
| American Repertory Ballet | 2012 | 0.0000000 |
| American Repertory Ballet | 2015 | 0.0000000 |
| American Repertory Ballet | 2016 | 0.0000000 |
| American Repertory Ballet | 2017 | 0.0000000 |
| BalletMet | 2013 | 0.0000000 |
| BalletMet | 2015 | 0.0000000 |
| BalletMet | 2016 | 0.0000000 |
| BalletMet | 2017 | 0.0000000 |
| BalletMet | 2020 | 0.0000000 |
| Fort Wayne Ballet | 2013 | 0.0000000 |
| The Washington Ballet | 2018 | 0.0000000 |
| The Washington Ballet | 2020 | 0.0000000 |
| The Alabama Ballet | 2012 | 0.0000000 |
| The Alabama Ballet | 2013 | 0.0000000 |
| The Alabama Ballet | 2014 | 0.0000000 |
| The Alabama Ballet | 2015 | 0.0000000 |
| The Sarasota Ballet | 2014 | 0.0000000 |
| The Sarasota Ballet | 2015 | 0.0000000 |
| Aspen Santa Fe Ballet | 2014 | 0.0000000 |
| Aspen Santa Fe Ballet | 2019 | 0.0000000 |
| Aspen Santa Fe Ballet | 2020 | 0.0000000 |
| Texas Ballet Theater | 2011 | 0.0000000 |
| Texas Ballet Theater | 2012 | 0.0000000 |
| Texas Ballet Theater | 2013 | 0.0000000 |
| Texas Ballet Theater | 2014 | 0.0000000 |
| Colorado Ballet | 2013 | 0.0000000 |
| Colorado Ballet | 2014 | 0.0000000 |
| Ballet Arizona | 2011 | 0.0000000 |
| Ballet Arizona | 2012 | 0.0000000 |
| Ballet Arizona | 2013 | 0.0000000 |
| Ballet West | 2011 | 0.0000000 |
| Eugene Ballet | 2012 | 0.0000000 |
| Eugene Ballet | 2013 | 0.0000000 |
| Eugene Ballet | 2014 | 0.0000000 |
| Eugene Ballet | 2015 | 0.0000000 |
| Eugene Ballet | 2016 | 0.0000000 |
| Eugene Ballet | 2017 | 0.0000000 |
| Eugene Ballet | 2018 | 0.0000000 |
| Eugene Ballet | 2019 | 0.0000000 |
| American Ballet Theatre | 2011 | -0.0293976 |
| Boston Ballet | 2015 | -0.0388779 |
| Nevada Ballet Theatre | 2020 | -0.0958192 |
| Milwaukee Ballet | 2019 | -0.2192253 |
| Ballet Hispanico | 2020 | -0.2921837 |
| Ballet Arizona | 2018 | -0.2958794 |
| The Washington Ballet | 2015 | -0.3307636 |
| Nevada Ballet Theatre | 2015 | -0.4171208 |
| San Francisco Ballet | 2019 | -0.4505953 |
| Houston Ballet | 2020 | -0.5394078 |
| Aspen Santa Fe Ballet | 2015 | -0.6154796 |
| Madison Ballet | 2019 | -0.6341596 |
| Pennsylvania Ballet | 2019 | -0.6773370 |
| Nevada Ballet Theatre | 2016 | -0.7510343 |
| Fort Wayne Ballet | 2018 | -0.8065878 |
| Nevada Ballet Theatre | 2021 | -0.8682968 |
| Houston Ballet | 2015 | -0.9290425 |
| Ballet West | 2012 | -0.9379652 |
| American Ballet Theatre | 2016 | -0.9486236 |
| Nevada Ballet Theatre | 2019 | -0.9524021 |
| Ballet West | 2018 | -1.0492992 |
| New York City Ballet | 2015 | -1.0935295 |
| Charlotte Ballet | 2019 | -1.1038242 |
| Nevada Ballet Theatre | 2017 | -1.1116605 |
| Milwaukee Ballet | 2016 | -1.1445611 |
| Pennsylvania Ballet | 2012 | -1.1858787 |
| Ballet Hispanico | 2015 | -1.2189376 |
| Ballet West | 2013 | -1.2456707 |
| Nevada Ballet Theatre | 2012 | -1.2797833 |
| Ballet Arizona | 2019 | -1.3078878 |
| Ballet Arizona | 2020 | -1.3712710 |
| Madison Ballet | 2012 | -1.3999721 |
| Ballet Quad Cities | 2019 | -1.4598540 |
| The Charleston Ballet | 2016 | -1.5786659 |
| Madison Ballet | 2016 | -1.6090293 |
| Fort Wayne Ballet | 2020 | -1.6147683 |
| Grand Rapids Ballet | 2012 | -1.6979640 |
| Dayton Ballet | 2016 | -1.9120081 |
| Miami City Ballet | 2015 | -1.9267945 |
| Pennsylvania Ballet | 2015 | -2.1126469 |
| Nashville Ballet | 2012 | -2.2699618 |
| Pacific Northwest Ballet | 2012 | -2.5481783 |
| Milwaukee Ballet | 2012 | -2.5900754 |
| The Charleston Ballet | 2015 | -2.8140235 |
| New York City Ballet | 2020 | -2.9450705 |
| American Ballet Theatre | 2018 | -3.0002561 |
| Nevada Ballet Theatre | 2014 | -3.0244949 |
| Charlotte Ballet | 2020 | -3.0415463 |
| Pittsburgh Ballet Theatre | 2020 | -3.0426410 |
| The Tallahassee Ballet | 2012 | -3.1998929 |
| American Ballet Theatre | 2014 | -3.2115030 |
| Houston Ballet | 2012 | -3.3717602 |
| Dayton Ballet | 2015 | -3.4304063 |
| The Washington Ballet | 2012 | -3.4429070 |
| Grand Rapids Ballet | 2016 | -3.4832176 |
| Ballet West | 2017 | -3.5593957 |
| Ballet Austin | 2016 | -3.6649665 |
| The Alabama Ballet | 2019 | -3.6897295 |
| Kansas City Ballet | 2018 | -3.7141912 |
| The Tallahassee Ballet | 2020 | -4.1994951 |
| Pennsylvania Ballet | 2016 | -4.2562307 |
| Ballet Quad Cities | 2020 | -4.5315904 |
| Tulsa Ballet | 2012 | -4.6514807 |
| Miami City Ballet | 2020 | -4.8106966 |
| Miami City Ballet | 2016 | -4.9799231 |
| Houston Ballet | 2016 | -4.9809760 |
| Ballet Hispanico | 2012 | -5.0486376 |
| Ballet Memphis | 2015 | -5.1492312 |
| The Tallahassee Ballet | 2016 | -5.8413323 |
| The Sarasota Ballet | 2018 | -5.8747682 |
| Ballet Memphis | 2016 | -5.9367915 |
| Ballet Memphis | 2019 | -6.1694703 |
| The Charleston Ballet | 2012 | -6.1998116 |
| Charlotte Ballet | 2012 | -6.3328889 |
| San Francisco Ballet | 2016 | -6.3667555 |
| The Alabama Ballet | 2018 | -6.3829029 |
| The Sarasota Ballet | 2012 | -6.7174246 |
| The Alabama Ballet | 2016 | -6.8163966 |
| Alvin Ailey American Dance Theater | 2016 | -7.2545116 |
| Pacific Northwest Ballet | 2016 | -7.3246969 |
| New York City Ballet | 2016 | -7.4654042 |
| Madison Ballet | 2015 | -7.5915755 |
| New York City Ballet | 2012 | -7.5962728 |
| San Francisco Ballet | 2020 | -8.4597794 |
| Pittsburgh Ballet Theatre | 2015 | -9.7519131 |
| Ballet Quad Cities | 2016 | -9.9700000 |
| Pittsburgh Ballet Theatre | 2012 | -10.4416904 |
| Ballet Memphis | 2020 | -11.6985509 |
| Pennsylvania Ballet | 2013 | -13.3856788 |
| Pittsburgh Ballet Theatre | 2016 | -13.8628328 |
| The Sarasota Ballet | 2013 | -14.6832902 |
| The Sarasota Ballet | 2011 | -15.1492335 |
| The Sarasota Ballet | 2019 | -15.1497071 |
| First State Ballet Theatre | 2013 | -16.1358788 |
| Atlanta Ballet | 2011 | -22.4396954 |
| The Washington Ballet | 2016 | -25.5508697 |
| Atlanta Ballet | 2020 | -28.5158513 |
| Atlanta Ballet | 2019 | -36.6916144 |
| Atlanta Ballet | 2014 | -38.6514489 |
| Atlanta Ballet | 2013 | -42.0972020 |
| Orlando Ballet | 2016 | -44.7242762 |
| Colorado Ballet | 2012 | -45.1865576 |
| The Washington Ballet | 2017 | -48.7379222 |
| First State Ballet Theatre | 2015 | -49.5289330 |
| The Washington Ballet | 2019 | -50.1144953 |
| First State Ballet Theatre | 2014 | -52.9562948 |
| San Francisco Ballet | 2011 | -55.3267726 |
| First State Ballet Theatre | 2018 | -72.7468454 |
| Aspen Santa Fe Ballet | 2018 | -90.9315940 |
| Orlando Ballet | 2020 | -90.9983829 |
| Nashville Ballet | 2019 | -94.4004512 |
| San Francisco Ballet | 2012 | -99.9832016 |
pct_change_ds %>%
filter(pct_change != Inf) %>%
select(organization_name, fiscal_year, pct_change) %>%
group_by(fiscal_year) %>%
summarize(total = n(),
avg = mean(pct_change),
med = median(pct_change),
sd = sd(pct_change)) %>%
make_table(title = "Percentage of Change in Endowment Balance By Year", col_names = c("Fiscal Year", "Total Companies", "Average % Change", "Median % Change", "Standard Deviation")) %>%
scroll_box(height = "450px")| Fiscal Year | Total Companies | Average % Change | Median % Change | Standard Deviation |
|---|---|---|---|---|
| 2010 | 1 | 0.3281092 | 0.3281092 | NA |
| 2011 | 31 | 23.2042543 | 8.9183455 | 64.52232 |
| 2012 | 36 | 39.5711928 | -1.2328310 | 242.88805 |
| 2013 | 40 | 14.4544304 | 4.8542974 | 38.48890 |
| 2014 | 40 | 56.4432194 | 8.2586243 | 299.10443 |
| 2015 | 42 | 93.2322610 | 0.1279159 | 481.13003 |
| 2016 | 43 | 24.2872831 | -0.7510343 | 98.50785 |
| 2017 | 43 | 27.5778232 | 8.6823347 | 89.08538 |
| 2018 | 44 | 15.9080630 | 4.8267305 | 46.13128 |
| 2019 | 43 | 5.6928617 | 1.1650569 | 32.37300 |
| 2020 | 39 | 7.2725415 | 0.2184921 | 44.93623 |
| 2021 | 6 | 98.6421536 | 27.8120030 | 167.76683 |
REMOVING investments
# Basic summary stats
pct_change_inv_ds %>%
filter(!is.na(pct_change) & pct_change != Inf) %>%
summarize(avg_pct_change = mean(pct_change),
median_pct_change = median(pct_change),
sd_pct_change = sd(pct_change))pct_change_inv_ds %>%
filter(!is.na(pct_change) & pct_change != Inf) %>%
group_by(EIN) %>%
summarize(avg_pct_change = mean(pct_change),
median_pct_change = median(pct_change),
sd_pct_change = sd(pct_change))# Basic histogram summarizing it
ggplot(pct_change_inv_ds, aes(x = pct_change)) +
geom_histogram(binwidth = 20) +
xlab("% Change\n(EYB - INV - BYB) / BYB * 100") +
ggtitle(label = "Percentage of Change in Endowment Balance", subtitle = "Red Line indicates 100%") +
theme_classic() +
geom_vline(xintercept = 100, color = "maroon", linetype = "dotted")## Histogram with cutoff of 200%
ggplot(pct_change_inv_ds, aes(x = pct_change)) +
geom_histogram(binwidth = 5) +
xlab("% Change\n(EYB - BYB) / BYB * 100") +
xlim(-100, 200) +
ggtitle(label = "Percentage of Change in Endowment Balance") +
theme_classic()pct_change_inv_ds %>%
filter(pct_change != Inf) %>%
select(organization_name, fiscal_year, pct_change) %>%
make_table(title = "Percentage of Change in Endowment Balance", col_names = c("Name", "Fiscal Year", "% Change")) %>%
scroll_box(height = "450px")| Name | Fiscal Year | % Change |
|---|---|---|
| Joffrey Ballet | 2015 | 3091.4016854 |
| Fort Wayne Ballet | 2014 | 1803.3224138 |
| First State Ballet Theatre | 2012 | 1448.0762683 |
| Ballet Arizona | 2016 | 586.1374894 |
| Orlando Ballet | 2017 | 547.7003508 |
| Ballet Arizona | 2015 | 493.1015099 |
| Ballet Hispanico | 2021 | 426.7571012 |
| Nashville Ballet | 2011 | 275.0123756 |
| First State Ballet Theatre | 2020 | 242.6848638 |
| Orlando Ballet | 2018 | 206.4099099 |
| Atlanta Ballet | 2017 | 202.3164983 |
| Milwaukee Ballet | 2011 | 197.6406871 |
| Nashville Ballet | 2016 | 187.7731485 |
| Grand Rapids Ballet | 2015 | 181.5004969 |
| Richmond Ballet | 2016 | 175.9261036 |
| Charlotte Ballet | 2013 | 151.2357429 |
| Joffrey Ballet | 2019 | 133.5419677 |
| Texas Ballet Theater | 2015 | 133.3333333 |
| The Charleston Ballet | 2013 | 118.3461667 |
| Dayton Ballet | 2018 | 111.2870455 |
| Ballet Memphis | 2012 | 99.9715525 |
| Ballet Austin | 2013 | 96.8010136 |
| Ballet Memphis | 2018 | 95.9769923 |
| Joffrey Ballet | 2020 | 86.1363009 |
| Texas Ballet Theater | 2018 | 85.6027576 |
| BalletMet | 2018 | 85.0249761 |
| Atlanta Ballet | 2016 | 76.1344084 |
| Ballet Austin | 2017 | 72.1291716 |
| First State Ballet Theatre | 2019 | 69.9900000 |
| Miami City Ballet | 2021 | 65.4636289 |
| The Tallahassee Ballet | 2011 | 56.0747664 |
| First State Ballet Theatre | 2016 | 53.2556470 |
| American Repertory Ballet | 2014 | 51.6506759 |
| Richmond Ballet | 2018 | 51.2753402 |
| Atlanta Ballet | 2012 | 47.9686134 |
| Dayton Ballet | 2019 | 45.1776417 |
| Richmond Ballet | 2020 | 43.9335422 |
| Ballet Hispanico | 2014 | 41.4922805 |
| The Sarasota Ballet | 2016 | 37.6855000 |
| American Repertory Ballet | 2013 | 34.4003625 |
| First State Ballet Theatre | 2017 | 32.2270270 |
| Aspen Santa Fe Ballet | 2017 | 27.9853981 |
| Richmond Ballet | 2019 | 26.8630003 |
| Ballet Des Moines | 2018 | 25.2500000 |
| Joffrey Ballet | 2016 | 24.4935699 |
| BalletMet | 2014 | 23.5425782 |
| BalletMet | 2019 | 22.9766213 |
| Richmond Ballet | 2017 | 22.7958845 |
| Kansas City Ballet | 2012 | 21.4853681 |
| New Mexico Ballet Company | 2019 | 21.2777356 |
| Miami City Ballet | 2018 | 20.0147230 |
| Ballet Memphis | 2014 | 19.3704481 |
| Boston Ballet | 2014 | 18.6852707 |
| Nashville Ballet | 2013 | 18.4613232 |
| The Tallahassee Ballet | 2014 | 18.0748529 |
| Ballet Memphis | 2017 | 16.5882353 |
| The Tallahassee Ballet | 2015 | 15.7290896 |
| Oregon Ballet Theatre | 2013 | 15.5103905 |
| Aspen Santa Fe Ballet | 2016 | 15.1095158 |
| Ballet Arizona | 2017 | 14.7588808 |
| Alvin Ailey American Dance Theater | 2012 | 14.0819093 |
| Orlando Ballet | 2019 | 13.7276516 |
| Atlanta Ballet | 2018 | 13.6920172 |
| Joffrey Ballet | 2018 | 12.3866961 |
| Kansas City Ballet | 2015 | 11.1856574 |
| Tulsa Ballet | 2019 | 10.7046483 |
| Grand Rapids Ballet | 2020 | 9.8477067 |
| Nashville Ballet | 2017 | 9.1265125 |
| Nevada Ballet Theatre | 2011 | 8.6980699 |
| Charlotte Ballet | 2015 | 8.3421522 |
| Kansas City Ballet | 2019 | 8.0361126 |
| Kansas City Ballet | 2011 | 7.7310912 |
| Tulsa Ballet | 2015 | 7.5126681 |
| New York City Ballet | 2018 | 7.4146906 |
| Boston Ballet | 2018 | 7.1601338 |
| Tulsa Ballet | 2018 | 7.0862626 |
| Aspen Santa Fe Ballet | 2012 | 7.0179265 |
| San Francisco Ballet | 2017 | 6.9661016 |
| Pittsburgh Ballet Theatre | 2018 | 6.5959063 |
| Alvin Ailey American Dance Theater | 2011 | 6.4956757 |
| Grand Rapids Ballet | 2019 | 6.4258755 |
| Joffrey Ballet | 2017 | 6.3995664 |
| Charlotte Ballet | 2016 | 6.2270094 |
| Oregon Ballet Theatre | 2015 | 6.1461577 |
| Oregon Ballet Theatre | 2014 | 6.0199280 |
| Dayton Ballet | 2017 | 5.9289833 |
| Aspen Santa Fe Ballet | 2011 | 5.8574809 |
| Boston Ballet | 2016 | 5.7408098 |
| Charlotte Ballet | 2014 | 5.3302887 |
| Aspen Santa Fe Ballet | 2013 | 4.4768989 |
| Pacific Northwest Ballet | 2020 | 4.3953178 |
| American Ballet Theatre | 2018 | 4.2860828 |
| Oregon Ballet Theatre | 2019 | 4.1823644 |
| Tulsa Ballet | 2016 | 4.0916360 |
| Kansas City Ballet | 2013 | 4.0820691 |
| Tulsa Ballet | 2017 | 3.7063554 |
| Oregon Ballet Theatre | 2017 | 3.4233093 |
| Pittsburgh Ballet Theatre | 2014 | 3.4148461 |
| Alvin Ailey American Dance Theater | 2013 | 3.0321922 |
| Fort Wayne Ballet | 2016 | 2.9551339 |
| Kansas City Ballet | 2016 | 2.9492075 |
| Richmond Ballet | 2015 | 2.8246016 |
| Oregon Ballet Theatre | 2016 | 2.6351387 |
| Ballet Austin | 2012 | 2.5771368 |
| Oregon Ballet Theatre | 2020 | 1.9913020 |
| Ballet Austin | 2020 | 1.8896472 |
| Pacific Northwest Ballet | 2017 | 1.8850513 |
| Boston Ballet | 2019 | 1.6442499 |
| Oregon Ballet Theatre | 2021 | 1.5619387 |
| Boston Ballet | 2020 | 1.5323016 |
| American Ballet Theatre | 2015 | 1.5318917 |
| Ballet Arizona | 2014 | 0.9960259 |
| Charlotte Ballet | 2017 | 0.9806814 |
| Ballet Des Moines | 2019 | 0.8898064 |
| BalletMet | 2011 | 0.8065975 |
| Atlanta Ballet | 2015 | 0.5635573 |
| Houston Ballet | 2017 | 0.2170576 |
| Oregon Ballet Theatre | 2018 | 0.1654999 |
| Eugene Ballet | 2020 | 0.0688889 |
| San Francisco Ballet | 2015 | 0.0255516 |
| Nevada Ballet Theatre | 2018 | 0.0132329 |
| Dance Theatre of Harlem | 2011 | 0.0000000 |
| Dance Theatre of Harlem | 2012 | 0.0000000 |
| Dance Theatre of Harlem | 2013 | 0.0000000 |
| Dance Theatre of Harlem | 2014 | 0.0000000 |
| Dance Theatre of Harlem | 2015 | 0.0000000 |
| Dance Theatre of Harlem | 2019 | 0.0000000 |
| Dance Theatre of Harlem | 2020 | 0.0000000 |
| American Repertory Ballet | 2012 | 0.0000000 |
| American Repertory Ballet | 2015 | 0.0000000 |
| American Repertory Ballet | 2016 | 0.0000000 |
| American Repertory Ballet | 2017 | 0.0000000 |
| BalletMet | 2015 | 0.0000000 |
| BalletMet | 2016 | 0.0000000 |
| BalletMet | 2017 | 0.0000000 |
| BalletMet | 2020 | 0.0000000 |
| Fort Wayne Ballet | 2015 | 0.0000000 |
| Grand Rapids Ballet | 2014 | 0.0000000 |
| Nashville Ballet | 2020 | 0.0000000 |
| Miami City Ballet | 2014 | 0.0000000 |
| The Alabama Ballet | 2012 | 0.0000000 |
| The Alabama Ballet | 2013 | 0.0000000 |
| The Alabama Ballet | 2014 | 0.0000000 |
| The Alabama Ballet | 2015 | 0.0000000 |
| The Sarasota Ballet | 2011 | 0.0000000 |
| The Sarasota Ballet | 2017 | 0.0000000 |
| Aspen Santa Fe Ballet | 2014 | 0.0000000 |
| Aspen Santa Fe Ballet | 2019 | 0.0000000 |
| Aspen Santa Fe Ballet | 2020 | 0.0000000 |
| Texas Ballet Theater | 2016 | 0.0000000 |
| Texas Ballet Theater | 2017 | 0.0000000 |
| Texas Ballet Theater | 2019 | 0.0000000 |
| Texas Ballet Theater | 2020 | 0.0000000 |
| Colorado Ballet | 2011 | 0.0000000 |
| Ballet Arizona | 2011 | 0.0000000 |
| Ballet Arizona | 2012 | 0.0000000 |
| Ballet Arizona | 2013 | 0.0000000 |
| Ballet West | 2011 | 0.0000000 |
| Ballet West | 2012 | 0.0000000 |
| Ballet West | 2013 | 0.0000000 |
| Ballet West | 2014 | 0.0000000 |
| Ballet West | 2015 | 0.0000000 |
| Ballet West | 2016 | 0.0000000 |
| Ballet West | 2017 | 0.0000000 |
| Ballet West | 2018 | 0.0000000 |
| Ballet West | 2019 | 0.0000000 |
| Ballet West | 2020 | 0.0000000 |
| Eugene Ballet | 2012 | 0.0000000 |
| Eugene Ballet | 2013 | 0.0000000 |
| Eugene Ballet | 2014 | 0.0000000 |
| Eugene Ballet | 2015 | 0.0000000 |
| Eugene Ballet | 2016 | 0.0000000 |
| Eugene Ballet | 2017 | 0.0000000 |
| Eugene Ballet | 2018 | 0.0000000 |
| Eugene Ballet | 2019 | 0.0000000 |
| Nevada Ballet Theatre | 2013 | 0.0000000 |
| Dance Theatre of Harlem | 2016 | -0.0388002 |
| Dance Theatre of Harlem | 2017 | -0.0388002 |
| Dance Theatre of Harlem | 2018 | -0.0388002 |
| Alvin Ailey American Dance Theater | 2014 | -0.0392102 |
| Texas Ballet Theater | 2011 | -0.0493333 |
| Charlotte Ballet | 2018 | -0.0581914 |
| Texas Ballet Theater | 2013 | -0.0666667 |
| Grand Rapids Ballet | 2013 | -0.0876163 |
| Texas Ballet Theater | 2014 | -0.1000000 |
| Texas Ballet Theater | 2012 | -0.1453333 |
| New York City Ballet | 2016 | -0.1864872 |
| San Francisco Ballet | 2018 | -0.1940437 |
| Colorado Ballet | 2014 | -0.2510000 |
| Colorado Ballet | 2015 | -0.2520000 |
| Alvin Ailey American Dance Theater | 2015 | -0.2569099 |
| BalletMet | 2012 | -0.3331681 |
| Colorado Ballet | 2013 | -0.3810000 |
| The Sarasota Ballet | 2020 | -0.4168927 |
| Alvin Ailey American Dance Theater | 2016 | -0.4368254 |
| Nashville Ballet | 2012 | -0.4551243 |
| Ballet Austin | 2014 | -0.4603608 |
| Alvin Ailey American Dance Theater | 2017 | -0.4696754 |
| Ballet Hispanico | 2016 | -0.5203856 |
| Pacific Northwest Ballet | 2015 | -0.5908373 |
| Aspen Santa Fe Ballet | 2015 | -0.6154796 |
| Pacific Northwest Ballet | 2012 | -0.6598631 |
| Ballet Arizona | 2020 | -0.6848327 |
| Nashville Ballet | 2015 | -0.6853998 |
| New Mexico Ballet Company | 2018 | -0.7077376 |
| Kansas City Ballet | 2014 | -0.8280620 |
| Miami City Ballet | 2020 | -0.9255126 |
| Pacific Northwest Ballet | 2013 | -0.9444040 |
| The Charleston Ballet | 2016 | -0.9866662 |
| San Francisco Ballet | 2014 | -0.9910720 |
| The Charleston Ballet | 2012 | -1.0318066 |
| Eugene Ballet | 2021 | -1.0345879 |
| New Mexico Ballet Company | 2020 | -1.0439065 |
| The Charleston Ballet | 2017 | -1.0549591 |
| Nevada Ballet Theatre | 2021 | -1.0575507 |
| The Washington Ballet | 2020 | -1.0929032 |
| The Charleston Ballet | 2018 | -1.1136875 |
| Dayton Ballet | 2016 | -1.1467761 |
| The Charleston Ballet | 2014 | -1.2317960 |
| Grand Rapids Ballet | 2012 | -1.3028661 |
| Miami City Ballet | 2016 | -1.3238250 |
| Nevada Ballet Theatre | 2017 | -1.3727029 |
| Nevada Ballet Theatre | 2015 | -1.3742294 |
| Nevada Ballet Theatre | 2012 | -1.4376258 |
| Miami City Ballet | 2017 | -1.4499121 |
| Nevada Ballet Theatre | 2016 | -1.4829021 |
| The Washington Ballet | 2018 | -1.4873926 |
| American Ballet Theatre | 2011 | -1.5314013 |
| The Charleston Ballet | 2011 | -1.5332290 |
| Pacific Northwest Ballet | 2018 | -1.5533495 |
| Boston Ballet | 2015 | -1.6149354 |
| The Tallahassee Ballet | 2016 | -1.6490278 |
| The Tallahassee Ballet | 2020 | -1.7058059 |
| Tulsa Ballet | 2020 | -1.7067692 |
| Nevada Ballet Theatre | 2020 | -1.7139215 |
| The Tallahassee Ballet | 2019 | -1.7488328 |
| The Tallahassee Ballet | 2018 | -1.8057031 |
| The Tallahassee Ballet | 2017 | -1.8123203 |
| New York City Ballet | 2015 | -1.8130845 |
| The Sarasota Ballet | 2012 | -1.8569979 |
| Milwaukee Ballet | 2015 | -1.9311545 |
| Tulsa Ballet | 2011 | -1.9614773 |
| New York City Ballet | 2017 | -1.9751171 |
| Milwaukee Ballet | 2018 | -2.0100044 |
| Milwaukee Ballet | 2016 | -2.0435436 |
| Milwaukee Ballet | 2014 | -2.1177693 |
| Milwaukee Ballet | 2017 | -2.1349908 |
| The Tallahassee Ballet | 2012 | -2.1823537 |
| Ballet Austin | 2019 | -2.2380197 |
| Nevada Ballet Theatre | 2019 | -2.2385659 |
| Houston Ballet | 2012 | -2.2434479 |
| Nashville Ballet | 2018 | -2.2783590 |
| Grand Rapids Ballet | 2011 | -2.3220564 |
| Houston Ballet | 2015 | -2.3336650 |
| The Tallahassee Ballet | 2013 | -2.4204703 |
| Milwaukee Ballet | 2012 | -2.4277671 |
| Milwaukee Ballet | 2013 | -2.4289560 |
| Ballet Arizona | 2018 | -2.4510904 |
| Alvin Ailey American Dance Theater | 2019 | -2.4754845 |
| Houston Ballet | 2019 | -2.4811062 |
| Pacific Northwest Ballet | 2011 | -2.4913273 |
| Pacific Northwest Ballet | 2019 | -2.5450559 |
| Ballet Austin | 2015 | -2.5456829 |
| Ballet Austin | 2018 | -2.5948054 |
| Fort Wayne Ballet | 2013 | -2.6191910 |
| American Ballet Theatre | 2020 | -2.6235825 |
| American Ballet Theatre | 2017 | -2.6279486 |
| Ballet Memphis | 2013 | -2.6974641 |
| BalletMet | 2013 | -2.8122552 |
| San Francisco Ballet | 2013 | -2.9086447 |
| Grand Rapids Ballet | 2016 | -2.9294626 |
| Milwaukee Ballet | 2019 | -2.9985679 |
| Boston Ballet | 2017 | -3.0275416 |
| Madison Ballet | 2013 | -3.0421945 |
| New York City Ballet | 2019 | -3.0471032 |
| Tulsa Ballet | 2012 | -3.0603148 |
| Madison Ballet | 2011 | -3.0784277 |
| Pittsburgh Ballet Theatre | 2019 | -3.0837881 |
| Alvin Ailey American Dance Theater | 2018 | -3.1458141 |
| Houston Ballet | 2016 | -3.1799179 |
| Ballet Austin | 2016 | -3.1962055 |
| Ballet Hispanico | 2015 | -3.2768327 |
| Boston Ballet | 2012 | -3.3201972 |
| Boston Ballet | 2011 | -3.3370689 |
| Pennsylvania Ballet | 2011 | -3.3399761 |
| Madison Ballet | 2014 | -3.3480506 |
| The Charleston Ballet | 2015 | -3.3875824 |
| Ballet Hispanico | 2017 | -3.4496830 |
| Houston Ballet | 2013 | -3.4766281 |
| Fort Wayne Ballet | 2018 | -3.4861746 |
| Charlotte Ballet | 2012 | -3.5101847 |
| The Alabama Ballet | 2020 | -3.5193077 |
| New York City Ballet | 2020 | -3.5223075 |
| Ballet Hispanico | 2019 | -3.5388308 |
| Pennsylvania Ballet | 2012 | -3.5450717 |
| Houston Ballet | 2014 | -3.5722904 |
| Ballet Hispanico | 2020 | -3.6378284 |
| American Ballet Theatre | 2012 | -3.6951598 |
| Ballet Memphis | 2015 | -3.7093455 |
| New York City Ballet | 2014 | -3.7144943 |
| Ballet Memphis | 2016 | -3.7888700 |
| Miami City Ballet | 2019 | -3.7915315 |
| Ballet Memphis | 2020 | -3.8335615 |
| Tulsa Ballet | 2013 | -3.8622251 |
| The Alabama Ballet | 2019 | -3.8811799 |
| Pennsylvania Ballet | 2018 | -3.8912045 |
| Pennsylvania Ballet | 2020 | -3.8933190 |
| Pennsylvania Ballet | 2019 | -3.9757122 |
| Miami City Ballet | 2013 | -3.9944003 |
| Ballet Memphis | 2011 | -4.0000000 |
| Pennsylvania Ballet | 2017 | -4.0018391 |
| Houston Ballet | 2020 | -4.0352545 |
| American Ballet Theatre | 2013 | -4.0480433 |
| Nevada Ballet Theatre | 2014 | -4.0666759 |
| New York City Ballet | 2013 | -4.0786837 |
| Fort Wayne Ballet | 2017 | -4.0886842 |
| Alvin Ailey American Dance Theater | 2020 | -4.1243918 |
| Nashville Ballet | 2014 | -4.1521909 |
| Ballet Memphis | 2019 | -4.2013624 |
| Charlotte Ballet | 2019 | -4.2365488 |
| Pennsylvania Ballet | 2015 | -4.2590021 |
| Pennsylvania Ballet | 2014 | -4.3330553 |
| American Ballet Theatre | 2016 | -4.3796387 |
| Kansas City Ballet | 2017 | -4.3897199 |
| New York City Ballet | 2012 | -4.4115201 |
| Houston Ballet | 2018 | -4.5670291 |
| Ballet Arizona | 2019 | -4.5855094 |
| Charlotte Ballet | 2020 | -4.6291277 |
| San Francisco Ballet | 2016 | -4.6507528 |
| Madison Ballet | 2012 | -4.6665736 |
| Pittsburgh Ballet Theatre | 2021 | -4.7030709 |
| Miami City Ballet | 2015 | -4.7185994 |
| Pacific Northwest Ballet | 2014 | -4.7609735 |
| Madison Ballet | 2020 | -4.7836803 |
| Ballet Hispanico | 2012 | -4.7885406 |
| Grand Rapids Ballet | 2017 | -4.7948908 |
| Richmond Ballet | 2013 | -4.8793429 |
| Pittsburgh Ballet Theatre | 2020 | -4.9093733 |
| Dayton Ballet | 2015 | -4.9439121 |
| Pacific Northwest Ballet | 2016 | -4.9507177 |
| Richmond Ballet | 2014 | -4.9885620 |
| The Alabama Ballet | 2016 | -4.9986909 |
| The Alabama Ballet | 2017 | -4.9999255 |
| Fort Wayne Ballet | 2019 | -5.0348542 |
| Madison Ballet | 2019 | -5.0381831 |
| Ballet Hispanico | 2013 | -5.0552449 |
| Fort Wayne Ballet | 2020 | -5.0721240 |
| Boston Ballet | 2013 | -5.1204623 |
| Grand Rapids Ballet | 2018 | -5.1685752 |
| The Washington Ballet | 2011 | -5.1983475 |
| Ballet Hispanico | 2011 | -5.2603795 |
| San Francisco Ballet | 2019 | -5.3065465 |
| Charlotte Ballet | 2011 | -5.3581636 |
| The Washington Ballet | 2012 | -5.3849301 |
| Madison Ballet | 2015 | -5.4760787 |
| Madison Ballet | 2018 | -5.4791930 |
| Pennsylvania Ballet | 2016 | -5.4872448 |
| Ballet Quad Cities | 2020 | -5.6644880 |
| New York City Ballet | 2011 | -5.6655590 |
| The Washington Ballet | 2013 | -5.6774923 |
| The Washington Ballet | 2014 | -5.8525690 |
| Madison Ballet | 2016 | -5.9477868 |
| Madison Ballet | 2017 | -5.9572663 |
| The Washington Ballet | 2015 | -5.9827004 |
| Ballet Hispanico | 2018 | -6.1313369 |
| Pittsburgh Ballet Theatre | 2012 | -6.1547435 |
| Houston Ballet | 2011 | -6.2005177 |
| Pittsburgh Ballet Theatre | 2017 | -6.5527789 |
| Pittsburgh Ballet Theatre | 2011 | -6.5693406 |
| Ballet Quad Cities | 2019 | -6.7947617 |
| American Ballet Theatre | 2019 | -6.8846524 |
| Ballet Quad Cities | 2018 | -6.9091692 |
| Ballet Quad Cities | 2017 | -7.0532045 |
| Pittsburgh Ballet Theatre | 2013 | -7.2217715 |
| American Ballet Theatre | 2010 | -7.3374978 |
| Tulsa Ballet | 2014 | -7.7686509 |
| The Sarasota Ballet | 2015 | -8.0136667 |
| Ballet Quad Cities | 2016 | -8.1500000 |
| San Francisco Ballet | 2020 | -8.8273535 |
| Pittsburgh Ballet Theatre | 2015 | -9.0623160 |
| The Alabama Ballet | 2018 | -9.3608502 |
| The Sarasota Ballet | 2018 | -9.5170855 |
| Pittsburgh Ballet Theatre | 2016 | -9.6760767 |
| The Sarasota Ballet | 2014 | -10.0118333 |
| American Ballet Theatre | 2014 | -10.1384374 |
| Kansas City Ballet | 2018 | -10.8708252 |
| The Sarasota Ballet | 2013 | -14.6832902 |
| First State Ballet Theatre | 2013 | -16.1358788 |
| The Sarasota Ballet | 2019 | -19.1999386 |
| Pennsylvania Ballet | 2013 | -23.4542637 |
| The Washington Ballet | 2016 | -26.9924442 |
| Atlanta Ballet | 2020 | -32.3489884 |
| Atlanta Ballet | 2011 | -33.2349745 |
| Atlanta Ballet | 2019 | -38.7833870 |
| Atlanta Ballet | 2014 | -43.5400727 |
| Orlando Ballet | 2016 | -44.3305946 |
| Atlanta Ballet | 2013 | -44.6403251 |
| Colorado Ballet | 2012 | -45.6020434 |
| First State Ballet Theatre | 2015 | -49.5289330 |
| The Washington Ballet | 2019 | -51.9275920 |
| First State Ballet Theatre | 2014 | -52.9562948 |
| The Washington Ballet | 2017 | -57.6457603 |
| San Francisco Ballet | 2011 | -58.6702757 |
| First State Ballet Theatre | 2018 | -72.7468454 |
| Aspen Santa Fe Ballet | 2018 | -90.9315940 |
| Orlando Ballet | 2020 | -91.0428942 |
| Nashville Ballet | 2019 | -94.2002001 |
| San Francisco Ballet | 2012 | -101.4981454 |
pct_change_inv_ds %>%
filter(pct_change != Inf) %>%
select(organization_name, fiscal_year, pct_change) %>%
group_by(fiscal_year) %>%
summarize(total = n(),
avg = mean(pct_change),
med = median(pct_change),
sd = sd(pct_change)) %>%
make_table(title = "Percentage of Change in Endowment Balance By Year", col_names = c("Fiscal Year", "Total Companies", "Average % Change", "Median % Change", "Standard Deviation")) %>%
scroll_box(height = "450px")| Fiscal Year | Total Companies | Average % Change | Median % Change | Standard Deviation |
|---|---|---|---|---|
| 2010 | 1 | -7.337498 | -7.3374978 | NA |
| 2011 | 31 | 13.177900 | -1.5332290 | 62.57769 |
| 2012 | 36 | 39.929583 | -1.1673363 | 242.90708 |
| 2013 | 40 | 6.990231 | -2.4247131 | 35.59458 |
| 2014 | 40 | 45.566905 | -0.1755000 | 285.55540 |
| 2015 | 42 | 91.353000 | -0.2544549 | 481.44766 |
| 2016 | 43 | 24.154434 | -0.4368254 | 97.43600 |
| 2017 | 43 | 19.912496 | 0.0000000 | 89.40665 |
| 2018 | 44 | 11.162350 | -0.4508906 | 46.15232 |
| 2019 | 43 | 1.888381 | -2.4754845 | 31.06880 |
| 2020 | 39 | 5.044147 | -1.0929032 | 45.02615 |
| 2021 | 6 | 81.164577 | 0.2636754 | 171.41046 |
Range of Endowment Percent Change
WITH investments
## Ranges of different percent change
# Reordering by standard deviation of pct_spend down
pct_change_ds_box <- pct_change_ds %>%
group_by(organization_name) %>%
filter(pct_change != Inf) %>%
summarize(sd = sd(pct_change, na.rm = TRUE)) %>%
right_join(pct_change_ds, by = "organization_name") %>%
select(organization_name, EIN, pct_change, sd) %>%
mutate(organization_name = reorder(organization_name, -sd, na.rm = TRUE))
## Unlimited
box_plot <- ggplot(pct_change_ds_box, aes(x = organization_name, y = pct_change)) +
geom_boxplot(aes(color = organization_name), show.legend = FALSE) +
geom_point(size = 1, alpha = 0.5) +
theme_bw() +
labs(title = "Range of Endowment Percent Change per Company",
x = "Dance Company",
y = "Percentage of Change in Endowment Balance") +
theme(axis.text.x = element_blank()) +
geom_hline(yintercept = 100, linetype = "dotted", color = "maroon")
ggplotly(box_plot) %>%
layout(showlegend = FALSE)##Limited to 100 for visibility
box_plot_lim <- ggplot(pct_change_ds_box, aes(x = organization_name, y = pct_change)) +
geom_boxplot(aes(color = organization_name), show.legend = FALSE) +
geom_point(size = 1, alpha = 0.5) +
theme_bw() +
labs(title = "Range of Endowment % Change (Max of 100) per Company",
x = "Dance Company",
y = "Percentage of Change in Endowment Balance") +
theme(axis.text.x = element_blank()) +
scale_y_continuous(breaks = scales::breaks_pretty(n = 20),
limit = c(-100,100))
ggplotly(box_plot_lim) %>%
layout(showlegend = FALSE)WITHOUT investments
## Ranges of different percent change
# reorder(organization_name, pull(summarize(spend_down, sd = sd(group_by(spend_down, pct_change)))), na.rm = TRUE)
# Reordering by standard deviation of pct_spend down
pct_change_inv_box <- pct_change_inv_ds %>%
group_by(organization_name) %>%
filter(pct_change != Inf) %>%
summarize(sd = sd(pct_change, na.rm = TRUE)) %>%
right_join(pct_change_ds, by = "organization_name") %>%
select(organization_name, EIN, pct_change, sd) %>%
mutate(organization_name = reorder(organization_name, -sd, na.rm = TRUE))
## Unlimited
box_plot_inv <- ggplot(pct_change_inv_box, aes(x = organization_name, y = pct_change)) +
geom_boxplot(aes(color = organization_name), show.legend = FALSE) +
geom_point(size = 1, alpha = 0.5) +
theme_bw() +
labs(title = "Range of Endowment Percent Change per Company",
x = "Dance Company",
y = "Percentage of Change in Endowment Balance") +
theme(axis.text.x = element_blank()) +
geom_hline(yintercept = 100, linetype = "dotted", color = "maroon")
ggplotly(box_plot_inv) %>%
layout(showlegend = FALSE)##Limited to 100 for visibility
box_plot_inv_lim <- ggplot(pct_change_inv_box, aes(x = organization_name, y = pct_change)) +
geom_boxplot(aes(color = organization_name), show.legend = FALSE) +
geom_point(size = 1, alpha = 0.5) +
theme_bw() +
labs(title = "Range of Endowment % Change (Max of 100) per Company",
x = "Dance Company",
y = "Percentage of Change in Endowment Balance") +
theme(axis.text.x = element_blank()) +
scale_y_continuous(breaks = scales::breaks_pretty(n = 20),
limit = c(-100,100))
ggplotly(box_plot_inv_lim) %>%
layout(showlegend = FALSE)Percent Change over Time
WITH investments
## Retrieving median values
pct_change_med <- pct_change_ds %>%
group_by(fiscal_year) %>%
summarize(median = median(pct_change, na.rm = TRUE)) %>%
mutate(organization_name = "Median")## Spend Down over Time
pct_change_plot <- pct_change_ds %>%
ggplot(aes(x = fiscal_year, y = pct_change,
group = organization_name, color = organization_name)) +
geom_line(alpha = 0.5) +
theme_bw() +
labs(y = "Percent Change",
x = "Fiscal Year",
title = "Percentage of Change in Endowment Balance",
subtitle = "By Fiscal Year") +
theme(plot.title = element_text(size = 10, face = "bold", hjust = .5),
axis.title = element_text(size = 12, face = "bold"),
plot.subtitle = element_text(size = 5, face = "italic", hjust = .5),
axis.text.x = element_text(size = 10, angle = 25),
strip.text = element_text(face="bold",size = 5),
legend.key.size = unit(1, 'mm'),
legend.text = element_text(size=7)) +
scale_y_continuous(labels = scales::comma_format(),
breaks = scales::pretty_breaks(n = 20)) +
geom_hline(yintercept = 100, linetype = "dotted", color = "gray") +
geom_point(data = pct_change_med, aes(x = fiscal_year, y = median), color = "black", size = 1)
ggplotly(pct_change_plot) ##Plot with Y scale between -100 and 100
limited_scale <- pct_change_ds %>%
ggplot(aes(x = fiscal_year, y = pct_change,
group = organization_name, color = organization_name)) +
geom_line(show.legend = FALSE, alpha = 0.5) +
theme_bw() +
labs(y = "Percent Change",
x = "Fiscal Year",
title = "Percentage of Change in Endowment Balance (max 100)",
subtitle = "By Fiscal Year") +
theme(plot.title = element_text(size = 10, face = "bold", hjust = .5),
axis.title = element_text(size = 12, face = "bold"),
plot.subtitle = element_text(size = 5, face = "italic", hjust = .5),
axis.text.x = element_text(size = 10, angle = 25),
strip.text = element_text(face="bold",size = 5),
legend.key.size = unit(1, 'mm'),
legend.text = element_text(size=7)) +
scale_y_continuous(labels = scales::comma_format(),
breaks = scales::pretty_breaks(n = 20),
limits = c(-100, 100)) +
geom_point(data = pct_change_med, aes(x = fiscal_year, y = median), color = "black", size = 1)
ggplotly(limited_scale)WITHOUT investments
## Retrieving median values
pct_change_inv_med <- pct_change_inv_ds %>%
group_by(fiscal_year) %>%
summarize(median = median(pct_change, na.rm = TRUE)) %>%
mutate(organization_name = "Median")## Spend Down over Time
pct_change_inv_plot <- pct_change_inv_ds %>%
ggplot(aes(x = fiscal_year, y = pct_change,
group = organization_name, color = organization_name)) +
geom_line(alpha = 0.5) +
theme_bw() +
labs(y = "Percent Change",
x = "Fiscal Year",
title = "Percentage of Change in Endowment Balance",
subtitle = "By Fiscal Year") +
theme(plot.title = element_text(size = 10, face = "bold", hjust = .5),
axis.title = element_text(size = 12, face = "bold"),
plot.subtitle = element_text(size = 5, face = "italic", hjust = .5),
axis.text.x = element_text(size = 10, angle = 25),
strip.text = element_text(face="bold",size = 5),
legend.key.size = unit(1, 'mm'),
legend.text = element_text(size=7)) +
scale_y_continuous(labels = scales::comma_format(),
breaks = scales::pretty_breaks(n = 20)) +
geom_hline(yintercept = 100, linetype = "dotted", color = "gray") +
geom_point(data = pct_change_inv_med, aes(x = fiscal_year, y = median), color = "black", size = 1)
ggplotly(pct_change_inv_plot) ##Plot with Y scale between -100 and 100
limited_scale_inv <- pct_change_inv_ds %>%
ggplot(aes(x = fiscal_year, y = pct_change,
group = organization_name, color = organization_name)) +
geom_line(show.legend = FALSE, alpha = 0.5) +
theme_bw() +
labs(y = "Percent Change",
x = "Fiscal Year",
title = "Percentage of Change in Endowment Balance (max 100)",
subtitle = "By Fiscal Year") +
theme(plot.title = element_text(size = 10, face = "bold", hjust = .5),
axis.title = element_text(size = 12, face = "bold"),
plot.subtitle = element_text(size = 5, face = "italic", hjust = .5),
axis.text.x = element_text(size = 10, angle = 25),
strip.text = element_text(face="bold",size = 5),
legend.key.size = unit(1, 'mm'),
legend.text = element_text(size=7)) +
scale_y_continuous(labels = scales::comma_format(),
breaks = scales::pretty_breaks(n = 20),
limits = c(-100, 100)) +
geom_point(data = pct_change_inv_med, aes(x = fiscal_year, y = median), color = "black", size = 0.5)
ggplotly(limited_scale_inv)Breaking Companies up by Behavior
Using only the dataset normalized for investments, as that has more consistency.
# Adding var for "Consistency"
## Between mean +/- SD
#inv_consist <- pct_change_inv_ds %>%
# group_by(organization_name) %>%
#filter(pct_change != Inf & pct_change != -Inf) %>%
# summarize(mean = mean(pct_change),
# sd = sd(pct_change)) %>%
# mutate(consistent = ifelse(between(mean + sd, -7, 7) | between(mean - sd, -7, 7), TRUE, FALSE))
## Checking if any value is outside of -7:7, can do with min/max
inv_consist <- pct_change_inv_ds %>%
group_by(organization_name) %>%
filter(pct_change != Inf & pct_change != -Inf) %>%
summarize(min = min(pct_change),
max = max(pct_change),
sd = sd(pct_change)) %>%
mutate(consistent = ifelse(between(min + sd, -7, 7) & between(max - sd, -7, 7), TRUE, FALSE),
#Manual inspection showed BQC should be marked as consistent but just didnt quite make it math-wise
consistent = ifelse(organization_name == "Ballet Quad Cities", TRUE, consistent))
## Adding consistency
inv_consist_ds <- inv_consist %>%
select(organization_name, consistent) %>%
right_join(pct_change_inv_ds, by = "organization_name") %>%
filter(pct_change != Inf & pct_change != -Inf)##plottinng
test <- ggplot(inv_consist_ds, aes(x = fiscal_year, y = pct_change,
group = organization_name, color = consistent)) +
geom_line(show.legend = TRUE, alpha = 0.3) +
theme_bw() +
labs(y = "Percent Change",
x = "Fiscal Year",
title = "Percentage of Change in Endowment Balance (max 100)",
subtitle = "By Fiscal Year") +
theme(plot.title = element_text(size = 10, face = "bold", hjust = .5),
axis.title = element_text(size = 12, face = "bold"),
plot.subtitle = element_text(size = 5, face = "italic", hjust = .5),
axis.text.x = element_text(size = 10, angle = 25),
strip.text = element_text(face="bold",size = 5),
legend.key.size = unit(1, 'mm'),
legend.text = element_text(size=7)) +
scale_y_continuous(labels = scales::comma_format(),
breaks = scales::pretty_breaks(n = 20),
limits = c(-100, 100)) +
geom_point(data = pct_change_inv_med, aes(x = fiscal_year, y = median), color = "black", size = 0.5) +
geom_hline(yintercept = 7, alpha = .5, linetype = "dotted") +
geom_hline(yintercept = -7, alpha = .5, linetype = "dotted")
testggplotly(test)inv_box <- inv_consist_ds %>%
group_by(organization_name) %>%
filter(pct_change != Inf) %>%
summarize(sd = sd(pct_change, na.rm = TRUE)) %>%
right_join(inv_consist_ds, by = "organization_name") %>%
select(organization_name, EIN, pct_change, sd, consistent) %>%
mutate(organization_name = reorder(organization_name, -sd, na.rm = TRUE))
## Unlimited
box_plot <- ggplot(inv_box, aes(x = organization_name, y = pct_change)) +
geom_boxplot(aes(color = consistent), show.legend = FALSE) +
geom_point(size = 1, alpha = 0.5) +
theme_bw() +
labs(title = "Range of Endowment Percent Change per Company",
x = "Dance Company",
y = "Percentage of Change in Endowment Balance") +
theme(axis.text.x = element_blank()) +
geom_hline(yintercept = 100, linetype = "dotted", color = "maroon")
ggplotly(box_plot) %>%
layout(showlegend = FALSE)##Limited to 100 for visibility
ggplot(inv_box, aes(x = organization_name, y = pct_change)) +
geom_boxplot(aes(color = consistent), show.legend = FALSE) +
geom_point(size = 1, alpha = 0.2) +
theme_bw() +
labs(title = "Range of Endowment % Change (Max of 100) per Company",
x = "Dance Company",
y = "Percentage of Change in Endowment Balance") +
theme(axis.text.x = element_blank()) +
scale_y_continuous(breaks = scales::breaks_pretty(n = 20),
limit = c(-100,100))Examining the Two Classes
Lists of Companies within Each Class
## Names in a table
# CONSISTENT ones
inv_consist %>%
filter(consistent == TRUE) %>%
select(-consistent) %>%
make_table(title = "Companies with Consistent Endowment Changes", col_names = c("Organization Name", "Minimum Change", "Maximum Change", "Standard Deviation")) %>%
scroll_box(height = "450px")| Organization Name | Minimum Change | Maximum Change | Standard Deviation |
|---|---|---|---|
| American Ballet Theatre | -10.1384374 | 4.2860828 | 4.0324901 |
| Ballet Quad Cities | -8.1500000 | -5.6644880 | 0.8835432 |
| Ballet West | 0.0000000 | 0.0000000 | 0.0000000 |
| Dance Theatre of Harlem | -0.0388002 | 0.0000000 | 0.0187423 |
| Eugene Ballet | -1.0345879 | 0.0688889 | 0.3302962 |
| Houston Ballet | -6.2005177 | 0.2170576 | 1.6879328 |
| Madison Ballet | -5.9572663 | -3.0421945 | 1.1388038 |
| Nevada Ballet Theatre | -4.0666759 | 8.6980699 | 3.2556331 |
| New York City Ballet | -5.6655590 | 7.4146906 | 3.6785695 |
| Pacific Northwest Ballet | -4.9507177 | 4.3953178 | 2.8264344 |
| Pittsburgh Ballet Theatre | -9.6760767 | 6.5959063 | 5.0398509 |
| The Alabama Ballet | -9.3608502 | 0.0000000 | 3.2690717 |
| Tulsa Ballet | -7.7686509 | 10.7046483 | 5.9757380 |
There are 13 companies which have ‘consistent’ endowment percent change.
## Names in a table
# INCONSISTENT ones
inv_consist %>%
filter(consistent == FALSE) %>%
select(-consistent) %>%
make_table(title = "Companies with Inconsistent Endowment Changes", col_names = c("Organization Name", "Minimum Change", "Maximum Change", "Standard Deviation")) %>%
scroll_box(height = "450px")| Organization Name | Minimum Change | Maximum Change | Standard Deviation |
|---|---|---|---|
| Alvin Ailey American Dance Theater | -4.1243918 | 14.081909 | 5.448452 |
| American Repertory Ballet | 0.0000000 | 51.650676 | 22.878143 |
| Aspen Santa Fe Ballet | -90.9315940 | 27.985398 | 32.123542 |
| Atlanta Ballet | -44.6403251 | 202.316498 | 77.865045 |
| Ballet Arizona | -4.5855094 | 586.137489 | 228.214430 |
| Ballet Austin | -3.1962055 | 96.801014 | 38.214646 |
| Ballet Des Moines | 0.8898064 | 25.250000 | 17.225258 |
| Ballet Hispanico | -6.1313369 | 426.757101 | 129.225939 |
| Ballet Memphis | -4.2013624 | 99.971553 | 41.557976 |
| BalletMet | -2.8122552 | 85.024976 | 27.183927 |
| Boston Ballet | -5.1204623 | 18.685271 | 7.187359 |
| Charlotte Ballet | -5.3581636 | 151.235743 | 47.968535 |
| Colorado Ballet | -45.6020434 | 0.000000 | 20.295490 |
| Dayton Ballet | -4.9439121 | 111.287046 | 48.991355 |
| First State Ballet Theatre | -72.7468454 | 1448.076268 | 483.621410 |
| Fort Wayne Ballet | -5.0721240 | 1803.322414 | 638.452734 |
| Grand Rapids Ballet | -5.1685752 | 181.500497 | 57.603893 |
| Joffrey Ballet | 6.3995664 | 3091.401685 | 1241.573466 |
| Kansas City Ballet | -10.8708252 | 21.485368 | 9.369251 |
| Miami City Ballet | -4.7185994 | 65.463629 | 22.940589 |
| Milwaukee Ballet | -2.9985679 | 197.640687 | 66.634896 |
| Nashville Ballet | -94.2002001 | 275.012376 | 108.069064 |
| New Mexico Ballet Company | -1.0439065 | 21.277736 | 12.791467 |
| Oregon Ballet Theatre | 0.1654999 | 15.510390 | 4.535373 |
| Orlando Ballet | -91.0428942 | 547.700351 | 261.257026 |
| Pennsylvania Ballet | -23.4542637 | -3.339976 | 6.153578 |
| Richmond Ballet | -4.9885620 | 175.926104 | 59.163609 |
| San Francisco Ballet | -101.4981454 | 6.966102 | 34.689496 |
| Texas Ballet Theater | -0.1453333 | 133.333333 | 47.525613 |
| The Charleston Ballet | -3.3875824 | 118.346167 | 42.371447 |
| The Sarasota Ballet | -19.1999386 | 37.685500 | 15.618410 |
| The Tallahassee Ballet | -2.4204703 | 56.074766 | 18.732869 |
| The Washington Ballet | -57.6457603 | -1.092903 | 21.377074 |
There are 33 companies which have ‘inconsistent’ endowment percent change.
Size of Companies in Each Class
##Getting employee data
source(here("GET_VARS.R"))##
## Attaching package: 'lubridate'
## The following objects are masked from 'package:base':
##
## date, intersect, setdiff, union
##Specifically reading in employee data
files <- dir( here("ballet_990_released_20230208"),
full.names = TRUE)
employ_data <- map_df(files, ~
get_df(variables = c("//Return//ReturnData//TotalEmployeeCnt"),
filename = .x
)) %>%
mutate(TotalEmployeeCnt = as.numeric(TotalEmployeeCnt)) %>%
left_join(names, by = "EIN")## Most recent years for each company
employ_data$fiscal_year = as.numeric(as.character(employ_data$fiscal_year))
most_recent_yrs <- employ_data %>%
group_by(organization_name) %>%
summarize(recent_year = max(fiscal_year, na.rm = TRUE)) %>%
left_join(employ_data, by = c("organization_name", "recent_year" = "fiscal_year"))
## Limiting to ONLY most recent year
most_recent_ds <- inv_consist_ds %>%
left_join(most_recent_yrs, by = "organization_name") %>%
filter(fiscal_year == recent_year)## Consistent
most_recent_ds %>%
filter(consistent == TRUE) %>%
filter(!is.na(TotalEmployeeCnt)) %>%
select(organization_name, TotalEmployeeCnt, EndYearBalanceAmt, recent_year) %>%
make_table("Size of Consistent Companies, by Employees and Endowment", col_names = c("Organization Name", "Total Employee Count", "End Year Balance Amount", "Fiscal Year")) %>%
scroll_box(height = "450px")| Organization Name | Total Employee Count | End Year Balance Amount | Fiscal Year |
|---|---|---|---|
| American Ballet Theatre | 493 | 26365262 | 2020 |
| Ballet Quad Cities | 4 | 8764 | 2020 |
| Ballet West | 541 | 2127314 | 2020 |
| Dance Theatre of Harlem | 149 | 33505 | 2020 |
| Eugene Ballet | 72 | 62150 | 2021 |
| Houston Ballet | 535 | 80123432 | 2020 |
| Madison Ballet | 41 | 932750 | 2020 |
| Nevada Ballet Theatre | 80 | 2470253 | 2021 |
| New York City Ballet | 1451 | 214442196 | 2020 |
| Pacific Northwest Ballet | 514 | 20779107 | 2020 |
| Pittsburgh Ballet Theatre | 235 | 10758728 | 2021 |
| The Alabama Ballet | 102 | 432673 | 2020 |
| Tulsa Ballet | 97 | 10614630 | 2020 |
## Inconsistent
most_recent_ds %>%
filter(consistent == FALSE) %>%
filter(!is.na(TotalEmployeeCnt)) %>%
select(organization_name, TotalEmployeeCnt, EndYearBalanceAmt, recent_year) %>%
make_table("Size of Inconsistent Companies, by Employees and Endowment", col_names = c("Organization Name", "Total Employee Count", "End Year Balance Amount", "Fiscal Year")) %>%
scroll_box(height = "450px")| Organization Name | Total Employee Count | End Year Balance Amount | Fiscal Year |
|---|---|---|---|
| Alvin Ailey American Dance Theater | 856 | 71754853 | 2020 |
| Aspen Santa Fe Ballet | 81 | 550000 | 2020 |
| Atlanta Ballet | 181 | 3356278 | 2020 |
| Ballet Arizona | 207 | 4606871 | 2020 |
| Ballet Austin | 283 | 8859387 | 2020 |
| Ballet Des Moines | 14 | 29858 | 2019 |
| Ballet Hispanico | 111 | 7481852 | 2021 |
| Ballet Memphis | 73 | 9982568 | 2020 |
| BalletMet | 209 | 535225 | 2020 |
| Boston Ballet | 664 | 18135662 | 2020 |
| Charlotte Ballet | 119 | 5670206 | 2020 |
| Dayton Ballet | 333 | 4108434 | 2019 |
| First State Ballet Theatre | 32 | 58253 | 2020 |
| Grand Rapids Ballet | 63 | 2171052 | 2020 |
| Joffrey Ballet | 348 | 8999109 | 2020 |
| Kansas City Ballet | 209 | 11847916 | 2019 |
| Miami City Ballet | 333 | 2949392 | 2021 |
| Milwaukee Ballet | 179 | 588056 | 2019 |
| New Mexico Ballet Company | 1 | 28897 | 2020 |
| Oregon Ballet Theatre | 235 | 65023 | 2021 |
| Orlando Ballet | 113 | 696082 | 2020 |
| Pennsylvania Ballet | 300 | 3290362 | 2020 |
| Richmond Ballet | 240 | 2301816 | 2020 |
| San Francisco Ballet | 731 | 113923812 | 2020 |
| Texas Ballet Theater | 406 | 329418 | 2020 |
| The Sarasota Ballet | 109 | 734309 | 2020 |
| The Tallahassee Ballet | 34 | 12524 | 2020 |
| The Washington Ballet | 235 | 310000 | 2020 |
Percent Change Within the Pandemic
WITH investments
## Pandemic Years
pct_change_plot <- pct_change_ds %>%
filter(fiscal_year %in% c("2018", "2019", "2020", "2021", "2022")) %>%
ggplot(aes(x = fiscal_year, y = pct_change,
group = organization_name, color = organization_name)) +
geom_line(show.legend = FALSE, alpha = 0.5) +
theme_bw() +
labs(y = "Percent Change",
x = "Fiscal Year",
title = "Percentage of Change in Endowment Balance",
subtitle = "Within Pandemic Years") +
theme(plot.title = element_text(size = 10, face = "bold", hjust = .5),
axis.title = element_text(size = 12, face = "bold"),
plot.subtitle = element_text(size = 5, face = "italic", hjust = .5),
axis.text.x = element_text(size = 10, angle = 25),
strip.text = element_text(face="bold",size = 5),
legend.key.size = unit(1, 'mm'),
legend.text = element_text(size=7)) +
scale_y_continuous(labels = scales::comma_format(),
breaks = scales::pretty_breaks(n = 20)) +
geom_hline(yintercept = 100, linetype = "dotted", color = "gray")
ggplotly(pct_change_plot) ## Table of available in-pandemic data
pct_change_ds %>%
filter(fiscal_year %in% c("2019", "2020", "2021", "2022")) %>%
select(organization_name, pct_change, fiscal_year) %>%
arrange(desc(fiscal_year)) %>%
make_table(title = "Percentage of Change in Endowment Balance within Pandemic Years", col_names = c("Name", "% Change", "Year")) %>%
scroll_box(height = "450px")| Name | % Change | Year |
|---|---|---|
| Ballet Hispanico | 432.1555786 | 2021 |
| Miami City Ballet | 103.3796951 | 2021 |
| Eugene Ballet | 35.3676599 | 2021 |
| Pittsburgh Ballet Theatre | 20.2563462 | 2021 |
| Oregon Ballet Theatre | 1.5619387 | 2021 |
| Nevada Ballet Theatre | -0.8682968 | 2021 |
| First State Ballet Theatre | 242.6848638 | 2020 |
| Joffrey Ballet | 90.8216917 | 2020 |
| Richmond Ballet | 39.8449675 | 2020 |
| Grand Rapids Ballet | 16.5116257 | 2020 |
| Ballet Austin | 8.9689362 | 2020 |
| American Ballet Theatre | 8.9365465 | 2020 |
| Ballet West | 8.0887426 | 2020 |
| Tulsa Ballet | 7.2630153 | 2020 |
| Boston Ballet | 6.8383787 | 2020 |
| The Sarasota Ballet | 5.3797096 | 2020 |
| Pacific Northwest Ballet | 5.2552006 | 2020 |
| Eugene Ballet | 2.0266667 | 2020 |
| Oregon Ballet Theatre | 1.9913020 | 2020 |
| Alvin Ailey American Dance Theater | 1.1173579 | 2020 |
| Madison Ballet | 1.0503166 | 2020 |
| Pennsylvania Ballet | 0.9848159 | 2020 |
| Nashville Ballet | 0.6340668 | 2020 |
| The Alabama Ballet | 0.5951924 | 2020 |
| Texas Ballet Theater | 0.5742863 | 2020 |
| New Mexico Ballet Company | 0.2184921 | 2020 |
| Dance Theatre of Harlem | 0.0000000 | 2020 |
| BalletMet | 0.0000000 | 2020 |
| The Washington Ballet | 0.0000000 | 2020 |
| Aspen Santa Fe Ballet | 0.0000000 | 2020 |
| Nevada Ballet Theatre | -0.0958192 | 2020 |
| Ballet Hispanico | -0.2921837 | 2020 |
| Houston Ballet | -0.5394078 | 2020 |
| Ballet Arizona | -1.3712710 | 2020 |
| Fort Wayne Ballet | -1.6147683 | 2020 |
| New York City Ballet | -2.9450705 | 2020 |
| Charlotte Ballet | -3.0415463 | 2020 |
| Pittsburgh Ballet Theatre | -3.0426410 | 2020 |
| The Tallahassee Ballet | -4.1994951 | 2020 |
| Ballet Quad Cities | -4.5315904 | 2020 |
| Miami City Ballet | -4.8106966 | 2020 |
| San Francisco Ballet | -8.4597794 | 2020 |
| Ballet Memphis | -11.6985509 | 2020 |
| Atlanta Ballet | -28.5158513 | 2020 |
| Orlando Ballet | -90.9983829 | 2020 |
| Joffrey Ballet | 146.9046722 | 2019 |
| First State Ballet Theatre | 69.9900000 | 2019 |
| Dayton Ballet | 47.3628143 | 2019 |
| Richmond Ballet | 34.8263002 | 2019 |
| New Mexico Ballet Company | 28.7289611 | 2019 |
| BalletMet | 22.9766213 | 2019 |
| Kansas City Ballet | 14.2884428 | 2019 |
| Tulsa Ballet | 14.0998602 | 2019 |
| Orlando Ballet | 13.8649901 | 2019 |
| American Ballet Theatre | 12.8340039 | 2019 |
| Grand Rapids Ballet | 11.2809947 | 2019 |
| Boston Ballet | 7.8186556 | 2019 |
| Ballet Des Moines | 6.2713554 | 2019 |
| Oregon Ballet Theatre | 4.1823644 | 2019 |
| Alvin Ailey American Dance Theater | 3.5551869 | 2019 |
| The Tallahassee Ballet | 3.4501860 | 2019 |
| Houston Ballet | 3.0126539 | 2019 |
| Ballet Austin | 2.7039028 | 2019 |
| Pacific Northwest Ballet | 2.5299841 | 2019 |
| Ballet West | 2.5020351 | 2019 |
| Ballet Hispanico | 1.5405288 | 2019 |
| Miami City Ballet | 1.1650569 | 2019 |
| Pittsburgh Ballet Theatre | 0.7669528 | 2019 |
| Texas Ballet Theater | 0.5813097 | 2019 |
| Fort Wayne Ballet | 0.4949803 | 2019 |
| New York City Ballet | 0.0809932 | 2019 |
| Dance Theatre of Harlem | 0.0000000 | 2019 |
| Aspen Santa Fe Ballet | 0.0000000 | 2019 |
| Eugene Ballet | 0.0000000 | 2019 |
| Milwaukee Ballet | -0.2192253 | 2019 |
| San Francisco Ballet | -0.4505953 | 2019 |
| Madison Ballet | -0.6341596 | 2019 |
| Pennsylvania Ballet | -0.6773370 | 2019 |
| Nevada Ballet Theatre | -0.9524021 | 2019 |
| Charlotte Ballet | -1.1038242 | 2019 |
| Ballet Arizona | -1.3078878 | 2019 |
| Ballet Quad Cities | -1.4598540 | 2019 |
| The Alabama Ballet | -3.6897295 | 2019 |
| Ballet Memphis | -6.1694703 | 2019 |
| The Sarasota Ballet | -15.1497071 | 2019 |
| Atlanta Ballet | -36.6916144 | 2019 |
| The Washington Ballet | -50.1144953 | 2019 |
| Nashville Ballet | -94.4004512 | 2019 |
pct_change_ds %>%
filter(fiscal_year %in% c("2019", "2020", "2021", "2022")) %>%
select(organization_name, pct_change, fiscal_year) %>%
group_by(fiscal_year) %>%
summarize(total_in_year = n())WITHOUT investments
## Pandemic Years
pct_change_plot_inv <- pct_change_inv_ds %>%
filter(fiscal_year %in% c("2018", "2019", "2020", "2021", "2022")) %>%
ggplot(aes(x = fiscal_year, y = pct_change,
group = organization_name, color = organization_name)) +
geom_line(show.legend = FALSE, alpha = 0.5) +
theme_bw() +
labs(y = "Percent Change",
x = "Fiscal Year",
title = "Percentage of Change in Endowment Balance",
subtitle = "Within Pandemic Years") +
theme(plot.title = element_text(size = 10, face = "bold", hjust = .5),
axis.title = element_text(size = 12, face = "bold"),
plot.subtitle = element_text(size = 5, face = "italic", hjust = .5),
axis.text.x = element_text(size = 10, angle = 25),
strip.text = element_text(face="bold",size = 5),
legend.key.size = unit(1, 'mm'),
legend.text = element_text(size=7)) +
scale_y_continuous(labels = scales::comma_format(),
breaks = scales::pretty_breaks(n = 20)) +
geom_hline(yintercept = 100, linetype = "dotted", color = "gray")
ggplotly(pct_change_plot_inv) ## Table of available in-pandemic data
pct_change_inv_ds %>%
filter(fiscal_year %in% c("2019", "2020", "2021", "2022")) %>%
select(organization_name, pct_change, fiscal_year) %>%
arrange(desc(fiscal_year)) %>%
make_table(title = "Percentage of Change in Endowment Balance within Pandemic Years", col_names = c("Name", "% Change", "Year")) %>%
scroll_box(height = "450px")| Name | % Change | Year |
|---|---|---|
| Ballet Hispanico | 426.7571012 | 2021 |
| Miami City Ballet | 65.4636289 | 2021 |
| Oregon Ballet Theatre | 1.5619387 | 2021 |
| Eugene Ballet | -1.0345879 | 2021 |
| Nevada Ballet Theatre | -1.0575507 | 2021 |
| Pittsburgh Ballet Theatre | -4.7030709 | 2021 |
| First State Ballet Theatre | 242.6848638 | 2020 |
| Joffrey Ballet | 86.1363009 | 2020 |
| Richmond Ballet | 43.9335422 | 2020 |
| Grand Rapids Ballet | 9.8477067 | 2020 |
| Pacific Northwest Ballet | 4.3953178 | 2020 |
| Oregon Ballet Theatre | 1.9913020 | 2020 |
| Ballet Austin | 1.8896472 | 2020 |
| Boston Ballet | 1.5323016 | 2020 |
| Eugene Ballet | 0.0688889 | 2020 |
| Dance Theatre of Harlem | 0.0000000 | 2020 |
| BalletMet | 0.0000000 | 2020 |
| Nashville Ballet | 0.0000000 | 2020 |
| Aspen Santa Fe Ballet | 0.0000000 | 2020 |
| Texas Ballet Theater | 0.0000000 | 2020 |
| Ballet West | 0.0000000 | 2020 |
| The Sarasota Ballet | -0.4168927 | 2020 |
| Ballet Arizona | -0.6848327 | 2020 |
| Miami City Ballet | -0.9255126 | 2020 |
| New Mexico Ballet Company | -1.0439065 | 2020 |
| The Washington Ballet | -1.0929032 | 2020 |
| The Tallahassee Ballet | -1.7058059 | 2020 |
| Tulsa Ballet | -1.7067692 | 2020 |
| Nevada Ballet Theatre | -1.7139215 | 2020 |
| American Ballet Theatre | -2.6235825 | 2020 |
| The Alabama Ballet | -3.5193077 | 2020 |
| New York City Ballet | -3.5223075 | 2020 |
| Ballet Hispanico | -3.6378284 | 2020 |
| Ballet Memphis | -3.8335615 | 2020 |
| Pennsylvania Ballet | -3.8933190 | 2020 |
| Houston Ballet | -4.0352545 | 2020 |
| Alvin Ailey American Dance Theater | -4.1243918 | 2020 |
| Charlotte Ballet | -4.6291277 | 2020 |
| Madison Ballet | -4.7836803 | 2020 |
| Pittsburgh Ballet Theatre | -4.9093733 | 2020 |
| Fort Wayne Ballet | -5.0721240 | 2020 |
| Ballet Quad Cities | -5.6644880 | 2020 |
| San Francisco Ballet | -8.8273535 | 2020 |
| Atlanta Ballet | -32.3489884 | 2020 |
| Orlando Ballet | -91.0428942 | 2020 |
| Joffrey Ballet | 133.5419677 | 2019 |
| First State Ballet Theatre | 69.9900000 | 2019 |
| Dayton Ballet | 45.1776417 | 2019 |
| Richmond Ballet | 26.8630003 | 2019 |
| BalletMet | 22.9766213 | 2019 |
| New Mexico Ballet Company | 21.2777356 | 2019 |
| Orlando Ballet | 13.7276516 | 2019 |
| Tulsa Ballet | 10.7046483 | 2019 |
| Kansas City Ballet | 8.0361126 | 2019 |
| Grand Rapids Ballet | 6.4258755 | 2019 |
| Oregon Ballet Theatre | 4.1823644 | 2019 |
| Boston Ballet | 1.6442499 | 2019 |
| Ballet Des Moines | 0.8898064 | 2019 |
| Dance Theatre of Harlem | 0.0000000 | 2019 |
| Aspen Santa Fe Ballet | 0.0000000 | 2019 |
| Texas Ballet Theater | 0.0000000 | 2019 |
| Ballet West | 0.0000000 | 2019 |
| Eugene Ballet | 0.0000000 | 2019 |
| The Tallahassee Ballet | -1.7488328 | 2019 |
| Ballet Austin | -2.2380197 | 2019 |
| Nevada Ballet Theatre | -2.2385659 | 2019 |
| Alvin Ailey American Dance Theater | -2.4754845 | 2019 |
| Houston Ballet | -2.4811062 | 2019 |
| Pacific Northwest Ballet | -2.5450559 | 2019 |
| Milwaukee Ballet | -2.9985679 | 2019 |
| New York City Ballet | -3.0471032 | 2019 |
| Pittsburgh Ballet Theatre | -3.0837881 | 2019 |
| Ballet Hispanico | -3.5388308 | 2019 |
| Miami City Ballet | -3.7915315 | 2019 |
| The Alabama Ballet | -3.8811799 | 2019 |
| Pennsylvania Ballet | -3.9757122 | 2019 |
| Ballet Memphis | -4.2013624 | 2019 |
| Charlotte Ballet | -4.2365488 | 2019 |
| Ballet Arizona | -4.5855094 | 2019 |
| Fort Wayne Ballet | -5.0348542 | 2019 |
| Madison Ballet | -5.0381831 | 2019 |
| San Francisco Ballet | -5.3065465 | 2019 |
| Ballet Quad Cities | -6.7947617 | 2019 |
| American Ballet Theatre | -6.8846524 | 2019 |
| The Sarasota Ballet | -19.1999386 | 2019 |
| Atlanta Ballet | -38.7833870 | 2019 |
| The Washington Ballet | -51.9275920 | 2019 |
| Nashville Ballet | -94.2002001 | 2019 |
pct_change_inv_ds %>%
filter(fiscal_year %in% c("2019", "2020", "2021", "2022")) %>%
select(organization_name, pct_change, fiscal_year) %>%
group_by(fiscal_year) %>%
summarize(total_in_year = n())